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Feature extraction from video frames

The program itself will save frames from a video file to a sequence of JPG images. There are four extraction methods to choose from, extract an image every number of frames, extract an image every number of seconds, take a total number of frames from the video or extract every single frame Most of the time, extracting CNN features from video is cumbersome. In fact, this usually requires dumping video frames into the disk, loading the dumped frames one by one, pre processing them and use a CNN to extract features on chunks of videos

Extract Frames From Video With VLC Player 1. Open VLC media player and click on the Tools from the menu bar and click on the Preferences option from the drop-down menu (Keyboard Shortcut: Ctrl + P). This will open the simple preferences settings Use VLC Player VLC player lets you extract a frame from a video. Before you can use the app to extract frames, you should trim your video down to the exact part you want to extract frames from. You will need to play the entire video in order to get the frames so it will take time The feature is extracted from the center of the video by using a 32-frames clip. If you want a stronger feature by covering more temporal information. For example, you want to extract features from 10 segments of the video and combine them I'm trying something like extracting audio features for each video frame. I know there are 30 video frames and 16000 audio frames per second in the video file. I'm using pyAudioAnalysis python lib to achieve the goal but no success. Here is my code

Extract Frame from Videos using OpenCV in Python | Extracting and Saving Frames in Python - YouTube In this video, we are going to build a simple python program that will helps us to extract frames.. FFMPEG has the ability to extract all frames from a video and save them as images, it also can extract frames at a lower frame rate than the source video. See here for a demonstration of what I think you're trying to do, and the arguments to give ffmpeg to do so A better method to extract the video frames to attempt to enhance them would be to use VLC. NOTE: You might need to run VLC as an administrator. To do this opposite click on the icon and select run as administrator. Create a folder to store your frames and copy the path to it. C:\Users\[USERNAME]\Desktop\Video Frames for example Extracting features from the output of video segmentation. Feature extraction is the time consuming task in CBVR. This can be overcome by using the multi core architecture. These mainly include features of key frames, objects, motions and audio/text features. Features of Key Frames

Take a video as input and break the video into frame by frame and save those frame. Now, number of operations can be performed on these frames. Like reversing the video file or crop the video etc. For playing video in reverse mode, we need only to store the frames in a list and iterate reverse in the list of frames Feature Requests » Frame extraction from video file have implemented tools to extract desired frames from a video, directly in their environment (no need to add another software in the procedure). Are some similar tools in the development pipes in Agisoft ? Would be a nice add on and help to retain customer In this video, we explain and demonstrate Verisurf Feature Extraction from 3D scan data with several different examples.More about Verisurf 2019: https://you.. Extract frames from all the videos in the training as well as the validation set Preprocess these frames and then train a model using the frames in the training set. Evaluate the model using the frames present in the validation set Once we are satisfied with the performance on the validation set, use the trained model to classify new videos

5 Ways to Extract Video Frames and Save to Images • Raymond

present a various method of key frame extraction proposed in the past. manifold. Al 1. INTRODUCTION Digital process of extracting the frames of the video which represent the content of the video is known as the key frame extraction. algorithm for extracting the key frames from the video. In this method, shots o A fundamental challenge of extracting information from videos is a viewer has to go through the complete video to understand the context, as opposed to an image where the viewer can extract information from a single frame.. If you want to extract frame and get the same resolution as the original, click the video thumbnail in the Media Library and then click the Play button in the Preview Window. Click the Camera icon to extract the frame, and the extracted frames will be saved automatically to the media library. Step 2: Extract frames from video Frame by Frame In this paper, a novel system for texture feature extraction of video frames using GLCM method is proposed. The design was focused on GLCM hardware realization and texture feature extraction from software. The results were cross checked with simulation results Abstract. The lip-reading recognition is reported with lip-motion features extracted from multiple video frames by three unsupervised learning algorithms, i.e., Principle Component Analysis (PCA), Independent Component Analysis (ICA), and Non-negative Matrix Factorization (NMF)

Feature Extraction aims to reduce the number of features in a dataset by creating new features from the existing ones (and then discarding the original features). These new reduced set of features should then be able to summarize most of the information contained in the original set of features Extracting Frames from a video #64340. SAMYAK99 opened this issue on Aug 21, 2020 · 2 comments. Labels. plugin proposal. Comments. darshankawar added in triage waiting for customer response labels on Aug 23, 2020. no-response bot removed the waiting for customer response label on Aug 24, 2020. darshankawar added plugin proposal and removed in. I'm trying to extract all frames of some videos (each of them contains around 13000 frames) with this code but it take gets too long to extract all of the frames. is there any more quick way Open the camera instead of the file using cv2.VideoCapture (0) and start extracting frames. Use: We can perform a number of operations on these frames like crop, flip, reverse etc. save them into a list and iterate over them to get cropped/flipped/reversed video. (See How you can make Video from images) Hope you enjoy reading

To detect the shots, feature extraction has to be done to verify the similarity and dissimilarity between two frames of a video. We have proposed a technique called SIFT for the creation of feature vector in a video [ 12 ]. 2.1 Scale Invariant Feature Transform It is an efficient and powerful feature extraction algorithm for frame matching Extracts video frame images and associated metadata from a FMV-compliant video stream. The extracted images can be added to a mosaic dataset or other tools and functions for further analysis

Current techniques extract a sequence of meaningful frames from different fragments of video. Key frames are taken not only from the beginning of each shot, but also from the middle and the end. The whole video can be fragmented into scenes, subscenes, and shots for future analysis and key frame extraction Machine learning technologies are augmenting or replacing traditional approaches to feature extraction. In this workshop, we'll first examine traditional machine learning techniques for feature extraction in ArcGIS such as support vector machine, random forest, and clustering. We'll then move on to leveraging cutting-edge deep learning frameworks for object detection and image classification. frame selection of video with faces [25]. With the enhanced feature extraction and learning capabilities brought by deep neural network (DNN), their frame selection scheme out-performed the rank-based approach [6] without extracting pre-defined face features and learned different weights for different feature vectors in their experiment. But.

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3.1. Face quality based key-frame extraction A conventional face recognition system is composed of three main processing procedures: face detection, feature extraction and face recognition [21]. Once a face gets de-tected, the system will extract the feature vectors like LBP and HOG of the face images. Next, the extracted feature vectors are. Über 7 Millionen englische Bücher. Jetzt versandkostenfrei bestellen This function called extract_frames() takes a video path, a path to a frames directory, and a few extras like whether we want to overwrite frames if they already exist, or only do every x many frames

I am looking for a Windows based open source method to extract specific frames from video files (*.avi). Ideally the method will be suited to R. I need to do this as I have annotated (many) video files using Solomon Coder. This is an open source program which, quickly and easily, allows for user specified frame by frame annotation 7 thoughts on Extract Each Frame from a Video File using OpenCV in Python Not needed 21 April, 2018 at 1:01 am. Frames are not stored in data. Data folder is empty. Reply. Kaleem Ullah 3 May, 2018 at 1:29 pm Roadmap (vote for features) About Docs Service status. Support the development of JSFiddle and get extra features . Extracting Keyframes (I-frames) from a Video [closed] By keyframes, I mean frames in which the encoder has written all pixels instead of just the diff pixels. For example, in Adobe Premiere Pro you can specify the maximum number of frames between Key Frames in the export UI here: Further research, here and here, leads me to believe that these. Extract Photos from your Video. change video... Choose video file... A video contains many photographs. Use this free (in-browser) tool to navigage frame-by-frame and extract the best photos

GitHub - antoine77340/video_feature_extractor: Easy to use

How to extract a frame during video upload using JavaScript. When a file is selected from the file system, use the URL object to create a url to the local video file. Load that URL into a video element. When the video has loaded into memory, draw a frame on a canvas object. Now export the frame rendered on the canvas into an image element (or. Let us see how to extract frames from a video in MATLAB. Approach : Import the video which is to be converted into frames into the current matlab environment. Extract the total number of frames in the video. Make an empty directory named frames before the execution. Run a for loop and start extracting the frames into the directory

How To Extract Frames From Video Using VLC Player - oTechWorl

When set to capture more than 1 frame, we will continue to read more frames from the video and write those images to output directory. Once requested number of frames have been captured, we break and the loop will terminate. 5. Run extract.py. If you followed this tutorial, your extract.py should look like this This paper presents a novel system for texture feature extraction of video frames using Gray Level Cooccurrence Matrix (GLCM).GLCM extraction is done using hardware. Texture is one of the important characteristics used in identifying regions of interest or objects in an image. GLCM is one of the statistical method of examining texture that considers the spatial relationship of pixels is the. Stabilize a video that was captured from a jittery platform. One way to stabilize a video is to track a salient feature in the image and use this as an anchor point to cancel out all perturbations relative to it. This procedure, however, must be bootstrapped with knowledge of where such a salient feature lies in the first video frame adjacent frames in a video often share a large proportion of similar pixels, most of these works utilise a dynamic framework which separates frames into key and non-key frames and produce their segmentation masks differently. As illustrated in Fig. 1 (up), a deep image segmentation model N is divided into a heavy feature extraction part Nfeat an Only extract the keywords from features, low performance of optical key frame presentation 8 6 Kale, A. et. al. [2013] Video Retrieval Using Automatically Extracted Audio Used speech recognition algorithm to extract keywords Limited to metadata and Audio, different Language may reduce performance 9 7 Hadi Yarmohammadi et. al. [2013] Content.

Towards key-frame extraction methods for 3D video: aPromac GT068E - 6

How to extract a frame from a video on Windows 1

Method #5: Extract features from each frame with a CNN and pass the sequence to an MLP Let's apply the same CNN extraction process as in the previous method, but instead of sending each piece of the sequence to an RNN, we'll flatten the sequence and pass the new (2,048 x 40) input vector into a fully connected network, AKA a multilayer. 3.2. Video feature extraction. To reduce the computational complexity and enhance the effectiveness, we use image features instead of raw video frames .For each frame, we compute their deep semantic features using a trained Visual Geometry Group (VGG) network .This representation can encode the semantic transition of the video and thus can be used for various tasks including key frame. Algorithm: The step-wise approach is as follows: Extract frames from the video. Stack the frames in an array where the final array dimensions will be (num_frames, image_width, image_height, num. Capture the frames of a video. Extract frames from the videos until a maximum frame count is reached. In the case, where a video's frame count is lesser than the maximum frame count we will pad the video with zeros. Note that this workflow is identical to problems involving texts sequences

8. Extracting video features from pre-trained models ..

Keras: Feature extraction on large datasets with Deep Learning. 2020-06-04 Update: This blog post is now TensorFlow 2+ compatible! In the first part of this tutorial, we'll briefly discuss the concept of treating networks as feature extractors (which was covered in more detail in last week's tutorial).. From there we'll investigate the scenario in which your extracted feature dataset is. The proposed computational framework for key-frame extraction is shown in Fig. 1.Working with wildlife video sequences, the feature scheme starts with image segmentation, followed by low-level feature extraction and classification of the image blocks extracted from image segments

Existing key-frame extraction methods are basically video summary oriented; yet the index task of key-frames is ignored. This paper presents a novel key-frame extraction approach which can be available for both video summary and video index. First a dynamic distance separability algorithm is advanced to divide a shot into subshots based on semantic structure, and then appropriate key-frames. This video frame recorder is easy to use. In spite of above mentioned features, you can access more editing filters without few clicks. Part 2: How to Extract and Record Frames from a Video Easily. Step 1 Add a video. Free download and install the video frame capture software on your Windows or Mac computer. Launch this program after the.

How to extract audio features for each video frame using

Once the file has been uploaded, open the editing window and click the 'Edit' button in order to start the frame extraction process. Go to the point in the video from where you want to extract the frame and click pause. Click the 'Full Screen' button -so that you get a large and clear screenshot- and click the 'Take a Snapshot. Huang, J, Li, X, Kesavadas, T & Yang, L 2019, Feature extraction of video data for automatic visual tool tracking in robot assisted surgery. in Proceedings of the 2019 4th International Conference on Robotics, Control and Automation, ICRCA 2019 - Workshop 2019 the 4th International Conference on Robotics and Machine Vision, ICRMV 2019. ACM International Conference Proceeding Series. To bridge it, this work combines image entropy and density clustering to exploit the key frames from hand gesture video for further feature extraction, which can improve the efficiency of recognition. Moreover, a feature fusion strategy is also proposed to further improve feature representation, which elevates the performance of recognition

Extract Frame from Videos using OpenCV in Python

Extracted distinct key frames are used as testing queries in classification phase, and input frames features are extracted using the CNN feature extraction module, and learn features are matched with distinct key frame features to obtain the best match frame which is considered as key in the output as a frame index number Medical images and videos are utilized to discover, diagnose and treat diseases. Managing, storing, and retrieving stored images effectively are considered important topics. The rapid growth of multimedia data, including medical images and videos, has caused a swift rise in data transmission volume and repository size. Multimedia data contains useful information; however, it consumes an.

python - How can I extract frames from a video at a

OpenCV has a number of built-in features that allow us to extract data from a video. One of the features we can get is the frames per second (FPS) there are in a video. Frames are the images that make up a video. A video is a series of images shown in sequence. The frames per second tells us how many images there are per second of video One way to stabilize a video is to track a salient feature in the image and use this as an anchor point to cancel out all perturbations relative to it. This procedure, however, must be bootstrapped with knowledge of where such a salient feature lies in the first video frame This online utility lets you extract frames from a GIF animation. When you load your gif, you can view it in the browser and capture one, several, or a range of frames. The extracted frames are placed on a rectangular grid and can be downloaded as a PNG image. Created by GIF experts from team Browserling Feature extraction is a part of the dimensionality reduction process, in which, an initial set of the raw data is divided and reduced to more manageable groups. So when you want to process it will be easier. The most important characteristic of these large data sets is that they have a large number of variables I need source code for how to apply quantization to video frames to extract the features from it??? create a grayscale 8bit bitmap. tavale 17-Sep-09 4:40. tavale: 17-Sep-09 4:40 : thank you for the code I want tell you can I create a 8bit grayscale bitmap from the frame that I extract from the video..thanks: Bitmap variable. ryan117 25-Jun-09 3.

Videos: Utilize the EC Funded CAVIAR project/IST 2001 37540 Clips from INRIA (1st videos) as our set of training and test datasets (i.e. training and test set of videos). Preprocessing: Extract images from those videos to create a set of training and test set of images Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are. My video file is stored in the f: drive, which I want to convert into frames (thumbnails) and then store the frames in my chosen location. Code: Program to read a video file and extract frames from it. #Import libraries import cv2 import os #Function to extract frames def extractFrames(pathIn, pathOut): #directory path, where my video images. Video indexes may be constructed based on visual features of key frames, and queries may be directed at key frames using image retrieval techniques [6]. • Video annotation: Video annotation is the extraction of the information about video, adding this information to the video which can help in browsing, searching, analysis, retrieval.

gimp - How can I extract and magnify video frames

  1. Extract photos from your video. Just import a video from your device and you can either take a frame from your video at a position or take a range of photos from your videos. Set the start and end range of the video plus how many frames you want to extract. All the images from the video will be placed on your phone
  2. This module handles the task(s) for key frame(s) extraction and video compression. Key-frames are defined as the representative frames of a video stream, the frames that provide the most accurate and compact summary of the video content. Frame extraction and selection criteria for key-frame extraction. Frame that are sufficiently different from.
  3. Sparse vs Dense Optical Flow. Sparse optical flow gives the flow vectors of some interesting features (say few pixels depicting the edges or corners of an object) within the frame while Dense optical flow, which gives the flow vectors of the entire frame (all pixels) - up to one flow vector per pixel.As you would've guessed, Dense optical flow has higher accuracy at the cost of being slow.
  4. I am working on a assignment key frames extraction in a video sequence Method that i am using as follows. ->extracts frames one by one. ->histogram difference between two consecutive frames using imhist () and. imabsdiff () ->calculate mean and standard deviation of difference and threshold. ->continue till end of video

  1. At this moment, x t and h t − 1 use the same content in the process of calculating low-level features. When the variable t equals to 2, x t represents the features of the second frame, and h t − 1 represents the output of the previous frame. Until t equals to 5, the corresponding features of lane lines in the 5 th frame is predicted
  2. Extracting HD Frames from Videos. With just one click, one can extract images from video clips in Wondershare Filmora9. Most significantly, you will get accurate frames without any annoying lag. To extract frames from your video clips, all you have to do is install the video editing software and then follow the instructions
  3. 3. The function will then tell you the number of total video frames and ask you to enter the frames that you want to extract. Note that the first frame is frame 0. The example video has 100 frames total, so you can enter any frames between 0 and 99. You can specify the frames you want to extract by entering a single number, using the : symbol.
  4. hi i need to get frames from mp4 video any one can help me with the library i tried the avifile.dll and it worked will with avi video but now i need to open mp4 video and grap frames (bmp) from it video frames Extraction. how to extract video frames features? Extracting frames from a video in WPF. Play video and extract frame. C Program.

Python Program to extract frames using OpenCV

  1. Step 2: Open your movie or video in VLC media player. The second step needed to extract frames from video in VLC is opening the file you want to capture. In Windows, click or tap on Media in the top left corner of the app to reveal a menu with options for loading videos from all kinds of sources: files, folders, discs, and even streams
  2. How to extract individual frames. To extract individual frames from a video file, start by opening up the Kdenlive application on your Linux desktop by searching for it in the app menu. Then, follow the step-by-step instructions outlined below. Step 1: Locate the Project button, and click on it with the mouse to access Kdenlive's.
  3. How to extract the frames from a video using VLC VLC has the ability to extract the frames from a video and will handle virtually anything you can throw at it. This tutorial will show you how. See this tutorial if you are using an old version of VLC (pre-Rincewind). 1. Create a folder to store your frames and copy the path to it
  4. Recently, I was working on a program to sample N frames from a source video, and then assign a score to each frame (from 0 to 1) in terms of thumbnail-worthiness. Before long, it became apparent that decoding video frames was one performance bottleneck. In this post, I would look into different ways of reading video frames with OpenCV and then speeding it up with multithreading
  5. g best. The two streams were trained separately and combined.
  6. Believe it or not the code to turn a frame of a video into an image element is not terribly complicated. Below is a simple function that can be used to get the an image element corresponding to a specific frame in a video: function getVideoImage(path, secs, callback) {. var me = this, video = document.createElement('video')
  7. def extract_frames (video_path, frames_dir, overwrite = False, start =-1, end =-1, every = 1): Extract frames from a video using OpenCVs VideoCapture:param video_path: path of the video:param frames_dir: the directory to save the frames:param overwrite: to overwrite frames that already exist?:param start: start frame:param end: end frame
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Frame extraction from video file - Metashap

  1. Step 4: After that declare the corresponding frame of the feature vector as key frame. Step 5: From all the ten clusters extract ten key frames by applying step 3 and step 4 on each cluster. 3.2 Texture, edge, and motion features extraction The next step in our proposed framework is extraction
  2. These instructions will allow you to convert frames from a video into image files, using VLC Media Player. For those looking to prove picture quality in a video or those just needing high quality screen captures of a video, this tutorial will provide instructions that anyone can follow
  3. You can use the Ground Truth frame splitting feature when creating a new labeling job in the console to extract video frames from video files (MP4 files). A series of video frames extracted from a single video file is referred to as a sequence of video frames
  4. In Lightroom, select the video clip that you're interested in and double click on it to open it in the preview pane. Click on the cog icon at the bottom of the preview to see more of the video and drag the playhead left or right (or click on the frame advance controls) to find the best image. Once you've found the image you want, click on.
  5. How to extract video frames from pipeline through gstreamer-1.0???. I've written the following code to extract video frames but now am stuck. Could anyone please help??? #include..

Feature Extraction - YouTub

to detect and track other small UAVs from a video. These ap-proaches extract the features in each individual frames and apply supervised learning techniques to classify the target objects in the training dataset [17]. The trained classifiers based on deep learn-ing (e.g., Convolutional Neural Networks or CNN) can improv Key frames are the frames of the video which contain some vital information. Extraction of these frames is one of the important task in video processing. Extraction of these key frames which reflects the actual contents of the video in very essential for efficient browsing and retrieval of the video sequence from a large database of video 4. CNN feature extraction in TensorFlow is now made easier using the tensorflow/models repository on Github. There are pre-trained VGG, ResNet, Inception and MobileNet models available here. I have used the following wrapper for convenient feature extraction in TensorFlow. You can just provide the tool with a list of images emotions in videos involve apex frame extraction (detecting the frame where the peak of an emotion is Figure.1 Procedure for emotion recognition expressed) [7] followed by feature extraction and classification. The number of frames varies from 65 to 100 for a 4 sec video. A video expressing emotio Sparse optical flow selects a sparse feature set of pixels (e.g. interesting features such as edges and corners) to track its velocity vectors (motion). The extracted features are passed in the optical flow function from frame to frame to ensure that the same points are being tracked

Step 2: Capture video frame with the Samsung Galaxy S8. Open a video via the gallery, which you have taken with your S8 and from which you want to extract a frame. Then tap this icon in the upper left corner of the Video Player. This will now capture a single image and save it in the gallery under Video Captures structure analysis is the Key -frame extraction, it provid e us with a good video summarization and browsing a large video collections. Key -frame is a frame or set of frames that having a good representation of the entire content of small video clip. It must contain most of the salient features of the represented video clip

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Video Classification Video Classification Model In Pytho

  1. Details and Options. VideoExtractFrames can be used for extracting frames from a video. Frames can be used as thumbnails, in thumbnail grids or can be used to inspect a video at desired times. Possible settings for time specification tspec include: t. a single frame at time t. { t 1, t 2, .
  2. Generate SIFT features. 15. Generate SIFT features • You take a 16×16 window of in-between pixels around the keypoint. You split that window into sixteen 4×4 windows. From each 4×4 window you generate a histogram of 8 bins. Each bin corresponding to 0-44 degrees, 45-89 degrees, etc. Gradient orientations from the 4×4 are put into.
  3. 3) Key Frame Extraction: Key frames are the frames which summarize the entire video. These frames are found by uniqueness among all extracted frames. To find unique frames, dissimilarity between the frames should be calculated [12]. This can be achieved by applying algorithms like SIFT or SURF. The procedure involves following steps
  4. Tip: If you want to adjust the features of the image, such as the color, or add watermark to the image, you can click on the Edit button to edit the video before you capture the frame. 2 Other Programs to Extract Video Frames VLC Media Player. VLC is a very popular media player available on different platforms

Extract frame is the most frustrating feature. Useless with proxies (switching the proxy off doesn't work for me) and sometimes it extracts totally different frame (a key frame, first frame of the video or a totally random one) Figure 5. Spatial Binning Intuition. 3. HOG (Histogram of Oriented Gradients)- The feature extraction techniques discussed above are pretty cool but certainly not much powerful as compared to HOG.HOG actually takes an image, divides it into various blocks in which we have cells, in cells we observe the pixels and extract the feature vectors from them YouTube-8M Feature Extraction and Model Inference. MediaPipe is a useful and general framework for media processing that can assist with research, development, and deployment of ML models. This example focuses on model development by demonstrating how to prepare training data and do model inference for the YouTube-8M Challenge speed of video feature extraction, feature encoding and ac-tion classification by two orders of magnitude at the cost of the order of 1-2 frames per second. This stands in a sharp contrast with the needs of large-scale video indexing and re-trieval in modern video archives. Fast video recognition i

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Video to Photo is the easiest way to extract Full HD frames from your videos. Videos are loaded directly from your Camera Roll to the Video to Photo app, and then you can inspect the video frame by frame and pick up the one you like to save as a still image. The photo will be saved at the exact same resolution as the source video (Full HD/4K/8K) 2.1. Sequential Key Frame Extraction. Current techniques for extracting key frames can be classified into four categories according to various measurements [3, 4].The comparison-based method sequentially compares each frame with the previously extracted key frame with feature differences python for video key frame extraction (based on inter-frame difference) In many scenes, we do not want or can not deal with each frame of the video picture, then we hope to be able to extract from the video out some important frames are processed, a process we call video key frame extraction Video Summarization gives flexibility to users to understand the content of video without watching the whole video itself. In this paper, video summaries are generated by extracting key frames of a video using visual features like SSIM, color histogram, moment measure and correlation measure • To digitize features on a video, start an edit session and use a feature template. • Output from the Extract Video Frames for Orthomosaic GP tool is meant to be further processed in orthorectification workflows, not standard ArcMap mosaicking of georeferenced imagery. 3.3 Known Issue